7/12/2026 at 6:19:18 PM
What worries me isn’t AI replacing experts, it’s that we may stop producing people who know enough to notice when AI is confidently wrong.by sachaa
7/13/2026 at 8:09:18 AM
Don't worry. A lot of people were captivated by computers and programming before it ever became profitable. A lot of them will continue to be, even after it does not pay well..by qsera
7/13/2026 at 7:45:46 AM
[dead]by rjnz199
7/12/2026 at 6:50:40 PM
> it’s that we may stop producing people who know enough to notice when AI is confidently wrong.The running-joke is that a LinkedIn-lunatic AI booster, with a Nano Banana-generated profile-pic, will immediately slide into the chat to tell you that that this is already a solved problem: just spin up another agent to do the work to verify the first agent. Token-cost-be-damned. And we laugh and downvote them to oblivion and carry on with our day.
But today I had some exposure to a SotA agentic team coding loop thingie which had been running almost hands-off for a few weeks on a (pretty serious) Win32+Direct3D-to-Emscripten+WebGL porting project - and I'm genuinely spooked at how well it all works; I mention this example because all the agents' processes involved a decently rigorous verification step: any time any agent confidently asserts something then it has to provide associated evidence, such as a unit test report, or build artefact, or external citation, and the system will spawn a new agent (perhaps using a different backing LLM) to verify the claim. I know a unit-test pass/fail isn't quite the same thing as, say, a medical AI agent confidently wrong about me having/not-having terminal spleen cancer, but the capability for a team-of-agents to be self-checking is definitely there.
----
Also, the past 3 years of AI/LLM/etc developments have taught me to never cling to any shortcoming or weakness they have because plenty of them do seem to have been solved or mitigated, either directly or indirectly.
by DaiPlusPlus
7/12/2026 at 8:27:00 PM
> any time any agent confidently asserts something then it has to provide associated evidenceAnd this is enforced by... another LLM? Seems like it would work alright until something is asserted implicitly and not categorized as an assertion.
by solid_fuel
7/12/2026 at 9:42:42 PM
It does happen. But this is why the “ralph loop” works: over dozens (or hundreds) of iterations, eventually every regression, implicit assumption, fake passing test, is noticed and fixed by another agent. The code slowly but continuously converges to a better state. I’m surprised myself, but haven’t seen it fall into chaos or degradation so far.by ricardobeat
7/13/2026 at 5:28:07 AM
I haven't seen a code base which hasn't fallen into degradation from that loop.From personal experience, any "correction" leads to an LLM writing more code, or stripping apart interfaces and mixing logic poorly, or adding some hidden control flow just to catch that edge case rather than the general case for that category of input.
by evolve-maz
7/13/2026 at 6:46:43 AM
same as in real life?by lrizzo
7/13/2026 at 7:37:40 PM
I wouldn't accept that junk from any engineer in my team.My experience with good developers has been:
- Create something a bit ugly which works
- As more use cases come in, refactor code and clean up old gnarly bits
LLMs tend to work architecture astronaut style mixed with a junior for implementation. Build theoretically good interfaces but then implement dependencies across all of them. And when changes happen, keep feeding that cycle.
by evolve-maz
7/13/2026 at 6:15:10 AM
But doesn't things like that happen with people? Take academy where some professor implicitly states "facts" or military or software development where some highly praised senior always has his last word...by AndrewThrowaway
7/13/2026 at 9:40:20 AM
Sure, but it goes wrong with people, too.https://en.wikipedia.org/wiki/Space_Shuttle_Challenger_disas...
by ben_w
7/13/2026 at 9:36:11 AM
> But today I had some exposure to a SotA agentic team coding loop thingie which had been running almost hands-off for a few weeks on a (pretty serious) Win32+Direct3D-to-Emscripten+WebGL porting project - and I'm genuinely spooked at how well it all works; I mention this example because all the agents' processes involved a decently rigorous verification step: any time any agent confidently asserts something then it has to provide associated evidence, such as a unit test report, or build artefact, or external citation, and the system will spawn a new agent (perhaps using a different backing LLM) to verify the claim. I know a unit-test pass/fail isn't quite the same thing as, say, a medical AI agent confidently wrong about me having/not-having terminal spleen cancer, but the capability for a team-of-agents to be self-checking is definitely there.It taking "a few weeks" of wall-clock runtime suggests to me that it's making a lot of mistakes that keep needing correction, you're seeing the output after it fixes them. FWIW, my experience with them includes just enough fragile self-made unit tests to be a problem for entirely hands-off work, despite what it gets right.
However, on the topic of time rather than quality: Last summer I decided to convert an old game from C++/SDL2 to JS/WebGL, and was doing that with manual copying each function one at a time to ChatGPT and then code reviewing each line by hand. The wall-clock speedup from proper agentic coding that has come since then, is so much much faster than me working like this, that the modern approach would have been done in less than a week if it had managed without making mistakes.
I might go back to that project. While I was enjoying the process of code archeology (the code being a mix of many platforms starting with 68k era classic MacOS software rendering and resource forks upwards), I had to focus on other things for a bit in the meanwhile, which is of course the actual benefit of code factories.
by ben_w
7/13/2026 at 5:28:02 AM
The one I saw that curled my toes was an LLM that would take the input of a text field and turn it into an entry into a workplace health and safety log, and attribute the results to a human.It only needs to be wrong once to cause a legal shitstorm. You also wont be getting a chance to merge in a change to roll in a second agent for consistency checks from prison.
by protocolture
7/12/2026 at 7:02:26 PM
How is the token-cost-be-damned part in the latter example?I do find that both porting and translation projects have a much higher signal given the ease of mapping to tokens, when there is a proven working source to refer to - the source itself provides the validation. In a new project, you don’t have that validation.
by taurath
7/12/2026 at 7:13:59 PM
> How is the token-cost-be-damned part in the latter example?It's there, but...
1. The project owner figured out a way to minimize token usage for agent claim verification tasks.
2. Verification agents used older and much cheaper models, including local models for the most trivial things.
3. They could afford it anyway; but I think it's an inevitability that the token-cost for a task will approach some limit for some quality threshold - concurrent with the dollar-cost-per-token shrinking over time as better hardware comes out.
> In a new project, you don’t have that validation.
I'm still trying to understand that part of the project's history, actually. Obviously the HTML5+WebGL+Emscripten+Etc entrypoint was a "new" project; one of the first things they did was build their own means of verification, I just don't know how that part worked-out in practice (besides the agents dogpiling in on TODO.md).
by DaiPlusPlus
7/12/2026 at 6:53:05 PM
It's agents all the way down~!by gedy
7/12/2026 at 7:51:02 PM
"Determined" -> "Probabilistic"by sandruso